Terrence Alsup

Terrence Alsup is a PhD candidate advised by Benjamin Peherstorfer.  He is interested in uncertainty quantification as well as the intersection of numerical analysis and machine learning.  His current work is on multi-fidelity methods for importance sampling and applications to Bayesian inverse problems.

Tristan Goodwill

Tristan Goodwill is a PhD student advised by Mike O’Neil. He works on fast and accurate numerical solvers for integral equations that arise in computational physics. Specifically, his current work focuses on extending existing solvers for electromagnetic scattering problems to work on a larger class of scatterers.

Jason Kaye

Jason Kaye received his PhD from the Courant Institute in January 2020, and is currently a Research Fellow in the Center for Computational Mathematics and the Center for Computational Quantum Physics at the Flatiron Institute. He works on fast and high-order numerical algorithms for PDEs and integral equations arising in computational physics, with a focus on the simulation of quantum mechanical systems.

Karina Koval

Karina Koval is PhD candidate advised by Georg Stadler. Her primary interests include numerical methods, optimization under uncertainty and uncertainty quantification. Currently her research involves inverse problems governed by partial differential equations.

Frederick Law

Freddy Law is a PhD student working with Antoine Cerfon. He is interested in numerical methods for PDE as well as uncertainty quantification, primarily for problems arising in computational physics. His current work is in the simulation of turbulent plasma flows.

Anthony S Trubiano

Anthony Trubiano is a PhD student working with Miranda Holmes-Cerfon. He is interested in the mathematical modeling of physical systems in various fields of science and the methods of applied and computational mathematics in analyzing them. Particular interests include stochastic analysis, statistical mechanics, Monte Carlo methods, and other numerical solution algorithms.  He is currently studying the behavior of hard sphere packings in the presence of a long range potential.


Robert Webber

Rob Webber is a Ph.D. student advised by Jonathan Weare. He studies Monte Carlo methods with applications in atmospheric science, electronic structure theory, molecular dynamics, and linear algebra.